Papers

• Neural Non-Equilibrium Hamiltonian Monte Carlo for Corrected Boltzmann Sampling (2026)
  Moxian Qian
  4.39
• Free energy landscape of Dense Associative Memory (2026)
  Sumedha et al.
  4.39
• Nuclear Quantum Effects as a Denoising Problem (2026)
  Weizhou Wang et al.
  4.39
• Learning To Act Through Evolution Of Neural Diversity In Random Neural Networks (2023)
  Joachim Winther Pedersen, Sebastian Risi
  2.26
• Conditional Entropy of Heat Diffusion on Temporal Networks (2026)
  Samuel Koovely et al.
  1.89
• Reinforcement Learning for Microcanonical Graph Ensemble with Assortativity Constraints (2026)
  Hoyun Choi et al.
  1.89
• Stochastic Resetting Accelerates Policy Convergence in Reinforcement Learning (2026)
  Jello Zhou et al.
  1.78
• Autonomous Discovery of the Ising Model's Critical Parameters with Reinforcement Learning (2026)
  Hai Man et al.
  1.67
• Reinforcement Learning for Quantum Technology (2026)
  Marin Bukov et al.
  1.67
• Boltzmann generators for amorphous particle systems (2025)
  Louis Grenioux et al.
  1.61
• Statistical physics of deep learning: Optimal learning of a multi-layer perceptron near interpolation (2025)
  Jean Barbier et al.
  1.50
• On the Separability of Information in Diffusion Models (2025)
  Akhil Premkumar
  1.44
• Controlling dynamics of stochastic systems with deep reinforcement learning (2025)
  Ruslan Mukhamadiarov
  1.06
• Maximum diffusion reinforcement learning (2023)
  Thomas A. Berrueta et al.
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